Friction Stir Welding (FSW) is a feasible welding process to join dissimilar materials due to its solid-state nature. In this study the FSW of 6061-T6 aluminum with pure Cu plates was performed with the objective of evaluating the effects of the FSW parameters on the microstructure and electrical properties. The processing parameters (rotational and traverse speeds) were established to reduce the common defects in the friction-stir welding process. Therefore, the obtained results validated the better mechanical properties and a smaller increase of the electrical resistivity. The rotational speeds used were of 1000, 1150, and 1300 rpm, and the traverse speeds of 20, 40, and 60 mm/min, with the purpose of varying the heat input of the process. The microstructural characterization revealed the presence of a mixture of aluminum and copper into the weld zone, along with copper particles and the formation of intermetallic compounds. It was found that the electrical resistivity of the joints ranged from 0.029 to 0.036 μΩ. The highest electrical resistivity values were obtained at the lowest traverse speed (20 mm/min) and the lowest resistivity values were obtained at highest traverse speed (60 mm/min).
This research evaluates the effect of temperature and time austempering on microstructural characteristics and hardness of ductile iron, validating the results by means of a statistical method for hardness prediction. Ductile iron was subjected to austenitization at 950 °C for 120 min and then to austempering heat treatment in a salt bath at temperatures of 290, 320, 350 and 380 °C for 30, 60, 90 and 120 min. By increasing austempering temperature, a higher content of carbon-rich austenite was obtained, and the morphology of the thin acicular ferrite needles produced at 290 °C turned completely feathery at 350 and 380 °C. A thickening of acicular ferrite needles was also observed as austempering time increased. An inversely proportional behavior of hardness values was thus obtained, which was validated through data analysis, statistical tools and a regression model taking temperature and time austempering as input variables and hardness as the output variable, which achieved a correlation among variables of about 97%. The proposal of a mathematical model for the prediction of hardness in austempered ductile iron represents a numerical approximation which validates the experimental results at 95.20%.
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